A Paper-Based Biomimetic Sensing Device for the Discrimination of Original and Fraudulent Cigarette Brands Using Mixtures of MoS2 Quantum Dots and Organic Dyes

In this study, we investigated the combined effects of MoS2 QDs’ catalytic properties and colorimetric responses organic reagents to create a sniffing device based on sensor array concept mammalian olfactory system. The aim was differentiate volatile compounds (VOCs) present in cigarette smoke. designed optical nose utilized for classification various VOCs. Unsupervised Principal Component Analysis (PCA) supervised Linear Discriminant (LDA) methods were employed data analysis. LDA analysis showed promising results, with 100% accuracy both training cross-validation. To validate sensor’s performance, assessed its ability discriminate between five brands, achieving set 82% cross-validation set. Additionally, focused studying four popular Iranian brands (Bahman Kootah, Omega, Montana Gold, Williams), including fraudulent samples. Impressively, developed achieved perfect distinguishing these detecting fraud. We further analyzed total 126 samples, original ones, using matrix size (126 × 27). resulting model demonstrated an 98%. Our proposed analytical procedure is characterized by efficiency, affordability, user-friendliness, reliability. selectivity exhibited positions it as valuable tool differentiating counterfeit cigarettes, thus aiding border control efforts worldwide.